OpenGradient Python SDK

A Python SDK for decentralized model management and inference services on the OpenGradient platform. The SDK enables programmatic access to our model repository and decentralized AI infrastructure.

Key Features

• Model management and versioning
• Decentralized model inference
• Support for LLM inference with various models
• End-to-end verified AI execution
• Command-line interface (CLI) for direct access

Model Hub

Browse and discover AI models on our Model Hub. The Hub provides:

• Registry of models and LLMs
• Easy model discovery and deployment
• Direct integration with the SDK

Installation

pip install opengradient

Note: Windows users should temporarily enable WSL when installing opengradient (fix in progress).

Getting Started

1. Account Setup

You'll need two accounts to use the SDK:

• Model Hub account: Create one at Hub Sign Up
• OpenGradient account: Use an existing Ethereum-compatible wallet or create a new one via SDK

The easiest way to set up your accounts is through our configuration wizard:

opengradient config init

This wizard will:

• Guide you through account creation
• Help you set up credentials
• Direct you to our Test Faucet for devnet tokens

2. Initialize the SDK

import opengradient as og
og.init(private_key="<private_key>", email="<email>", password="<password>")

3. Basic Usage

Browse available models on our Model Hub or create and upload your own:

# Create and upload a model
og.create_model(
    model_name="my-model",
    model_desc="Model description",
    model_path="/path/to/model"
)

# Run inference
inference_mode = og.InferenceMode.VANILLA
result = og.infer(
    model_cid="your-model-cid",
    model_inputs={"input": "value"},
    inference_mode=inference_mode
)

4. Examples

See code examples under examples.

CLI Usage

The SDK includes a command-line interface for quick operations. First, verify your configuration:

opengradient config show

Run a test inference:

opengradient infer -m QmbUqS93oc4JTLMHwpVxsE39mhNxy6hpf6Py3r9oANr8aZ \
    --input '{"num_input1":[1.0, 2.0, 3.0], "num_input2":10}'

Use Cases

1. Off-chain Applications: Use OpenGradient as a decentralized alternative to centralized AI providers like HuggingFace and OpenAI.

2. Model Development: Manage models on the Model Hub and integrate directly into your development workflow.

Documentation

For comprehensive documentation, API reference, and examples, visit:

• OpenGradient Documentation
• API Reference

Support

• Run opengradient --help for CLI command reference
• Visit our documentation for detailed guides
• Join our community for support